Literature DB >> 29967647

Observational Study of the Association between TCM Zheng and Types of Coronary Artery Stenosis: Protocol of a Multicenter Case Series Study.

Chao Liu1,2, Guang Chen1,2, Dan Liu1, Shaoping Nie3, Xiao Wang3, Xinsheng Huang3, Haitao Li3, Yi Li4, Shihua Luo4, Guoan Zhao5, Fei Lin5, Haoqiang He1,2, Jun Li1, Yanwei Xing1, Zhenpeng Zhang1, Jie Wang1.   

Abstract

BACKGROUND: Coronary artery stenosis is the major pathological change of coronary heart disease (CHD). Within the framework of traditional Chinese medicine (TCM) theory, some kinds of TCM Zheng could exist in patients with CHD; accordingly, TCM practitioners could provide appropriate TCM therapy. However, little is known about the association between TCM Zheng and types of coronary artery stenosis. Such knowledge could help improve the accuracy and effectiveness of efforts to combine CHD treatment with TCM therapy. Therefore, the aim of this study is to determine the association between TCM Zheng and types of coronary artery stenosis. METHODS AND
DESIGN: This is a multicenter, large sample, case series study in 4 tertiary A hospitals from 3 provinces in China. A total of 3,000 eligible patients diagnosed with atherosclerosis or CHD and selected to undergo coronary angiography (CAG) will be enrolled in this study. We will use electronic case report forms (eCRF) to collect information, including baseline characteristics, TCM symptoms, CAG results, and GRACE scores according to standard operating procedures (SOP). Data will be analyzed by SPSS 20.0. ETHICS: This study is approved by the Ethics Committee of Guang'anmen Hospital of the China Academy of Chinese Medical Sciences (no. 2017-058-KY-01) and is registered with chictr.org (registration number ChiCTR-ROC-17013221).

Entities:  

Year:  2018        PMID: 29967647      PMCID: PMC6008665          DOI: 10.1155/2018/2564914

Source DB:  PubMed          Journal:  Evid Based Complement Alternat Med        ISSN: 1741-427X            Impact factor:   2.629


1. Introduction

Coronary heart disease (CHD) is currently the leading cause of death worldwide. According to an analysis of the causes of death and disease burden in the global population over the past 20 years, the number of deaths caused by CHD worldwide was 7,029,300 in 2010, accounting for 13% of total deaths [1]. According to the 2016 report on cardiovascular disease in China, the number of deaths from CHD was 11 million in 2015, the death rate of CHD in urban residents was 110.67/100 thousand, and the mortality rate of rural residents was 110.91/100 thousand in 2015. In addition, the total cost of hospitalization due to acute myocardial infarction represented an average annual growth of 30.13% since 2004 [2]. Increasing burden of CHD has become a major public health problem; thus, improvements in the prevention and treatment of CHD are urgently needed. Traditional Chinese medicine (TCM) has always been an essential part of the health care service system in China. It is well known that TCM practitioners usually prescribe herbal formulas or provide other TCM therapies based on Zheng differentiation of every patient using four diagnostic methods, including inspection, listening and smelling, inquiry, and palpation of the pulses. For CHD, a high-quality systematic review [3] concluded that treating CHD with some of the herbs used in TCM might be effective in alleviating angina symptoms, myocardial perfusion abnormalities, or neurological deficit. Furthermore, TCM might have the potential benefit of reducing major adverse cardiac events [4]. In addition, a large number of studies pertaining to the mechanism of herbal medications have shown that the herbs used to treat CHD address such functions as dilating blood vessels, improving microcirculation, reducing blood viscosity, regulating blood lipids, and enhancing energy metabolism and anti-inflammation [5]. However, it is worth mentioning that if TCM doctors had a comprehensive understanding of the difference in Zheng distribution of different types of CHD and stratifications of the Global Registry of Acute Coronary Events (GRACE) score, there might be less therapeutic error, and treatments might be more target-specific. Based on the degree of stenosis and treatment options, coronary stenosis can be divided into 5 types, including atherosclerosis with less than 30% stenosis, borderline coronary lesion with 30% to 70% stenosis, scheduled to undergo percutaneous coronary intervention (PCI), scheduled to undergo coronary artery bypass grafting (CABG), and being unable to undergo revascularization. There are different types of CHD, such as borderline artery lesion, acute coronary syndrome needing PCI and severe artery stenosis demanding CABG, and different stratifications of GRACE score, and these varying types mean different pathology, prognosis, and clinical risk. Thus, obtaining the association between TCM Zheng and types of coronary artery stenosis and GRACE score is crucial to advance the treatment of CHD by TCM. Although some of the recent studies focused on Zheng distributions in CHD patients based on investigations using clinical epidemiology, the association between TCM Zheng and types of coronary artery stenosis and GRACE score remains obscure. Therefore, we planned to carry out a multicenter large-sample case series study among four tertiary A hospitals in China to detect the association between TCM Zheng and types of coronary artery stenosis and GRACE score.

2. Objective

The study aims to determine the association between TCM Zheng and types of coronary artery stenosis and to determine the association between TCM Zheng and GRACE score.

3. Methods and Design

3.1. Study Design

This study is a multicenter, large sample, case series study. The Declaration of Helsinki and Good Clinical Practice (GCP) Guidelines are regarded as the principle of this clinical study. The protocol, informed consent, and electronic case report form (eCRF) of this study have been reviewed and approved by the Ethics Committee of Guang'anmen Hospital of the China Academy of Chinese Medical Sciences (no. 2017-058-KY-01). The participants' information and privacy will be strictly protected. Written informed consent will be obtained from each participant before the clinical information is collected. This study was registered at the Chinese Clinical Trial Registry on November 2, 2017, in both Chinese and English editions; the registration number was ChiCTR-ROC-17013221. The study design is briefly described in Figure 1.
Figure 1

Study flow chart. CHD: coronary heart disease; TCM: traditional Chinese medicine; CAG: coronary angiography; PCI: percutaneous coronary intervention; CABG: coronary artery bypass grafting.

3.2. Subject Recruitment

The patients had a diagnosis of coronary atherosclerosis or CHD. Normally, CHD includes borderline coronary lesion, stable angina pectoris (SAP), unstable angina (UA), non-ST-segment-elevation myocardial infraction (NSTEMI), and ST-segment-elevation myocardial infraction (STEMI); these conditions will be included in this case series study. All the patients will be enrolled from November 2017 to December 2018 at four hospitals, identified in Table 1. Three thousand eligible participants will be recruited from these four sites according to the inclusion and exclusion criteria.
Table 1

The hospitals participating in this study.

CodeParticipating CenterCodeParticipating Center
01Guang'anmen Hospital, China Academy of Chinese Medical Sciences03Yunnan Provincial Hospital of Traditional Chinese Medicine
02Beijing Anzhen Hospital Capital Medical University04The First Affiliated Hospital of Xinxiang Medical University

3.3. Diagnostic Criteria

3.3.1. Traditional Chinese Medicine Diagnostic Criteria of CHD Zheng

TCM Zheng of each participant will be estimated by two TCM experts referring to the “National Standard Clinical Terminology of Traditional Chinese Medical Diagnosis and Treatment–Syndromes (GB/T 16751.2-1997)” and “Traditional Chinese Medicine Syndrome Differentiation Criteria of Coronary Heart Disease” [6]. These two diagnostic criteria involve all the simple Zheng. Permutations and combinations of these simple Zheng are flexible and could encompass all the complex clinical settings. The interrater reliability of diagnosing TCM Zheng will be evaluated using the kappa statistic.

3.3.2. Diagnostic Criteria of CHD

The diagnostic criteria of different types of CHD will refer to the “Guideline for the Diagnosis and Management of Patients with Stable Ischemic Heart Disease” [7] (2012 edition), the “Guideline for the Management of Patients with Non-ST-Elevation Acute Coronary Syndromes” [8] (2014 edition), and the “Guideline for the Management of ST-Elevation Myocardial Infarction” [9] (2013 edition). To establish whether patients with CHD undergo revascularization (PCI or CABG) and whether patients are unable to undergo revascularization due to contraindications, we will refer to “Guidelines on Myocardial Revascularization” [10] (2011 edition). Specifically, we list the indications for revascularization of stable coronary artery disease (SCAD) patients and recommendations for the type of revascularization of SCAD patients in Tables 2 and 3, respectively.
Table 2

Indications for revascularization in patients with stable coronary artery disease.

Extent of CHDClassLevel
For prognosis
 Left main disease with stenosis >50%IA
 Any proximal LAD stenosis >50%IA
 Two-vessel or three-vessel disease with stenosis >50% with impaired LV function (LVEF<40%)IA
 Large area of ischaemia (>10% LV)IA
 Single remaining patent coronary artery with stenosis >50%IB
For symptomsIC
 Any coronary stenosis >50% in the presence of limiting angina or angina equivalent, unresponsive to medical therapyIA

LAD: left anterior descending coronary artery; LV: left ventricular.

Table 3

Recommendation for type of revascularization (CABG or PCI) in patients with stable coronary artery disease.

Extent of CHDCABGPCI
ClassLevelClassLevel
One- or two-vessel disease without proximal LAD stenosisIIbCIC
One-vessel disease with proximal LAD stenosisIAIA
Two-vessel disease with proximal LAD stenosisIBIC
Left main disease with a SYNTAX score 22IBIB
Left main disease with a SYNTAX score 23-32IBIIaB
Left main disease with a SYNTAX score >32IBIIIB
Three-vessel disease with a SYNTAX score 22IAIB
Three-vessel disease with a SYNTAX score 23-32IAIIIB
Three-vessel disease with a SYNTAX score >32IAIIIB

3.4. Inclusion and Exclusion Criteria

3.4.1. Inclusion Criteria

Inclusion criteria include the following: Patients with coronary atherosclerosis or with CHD. Planned coronary angiography (CAG). Participant aged from 18 to 80 years. Participants who voluntarily signed the informed consent.

3.4.2. Exclusion Criteria

Exclusion criteria include the following: Participants with acute infection, trauma, burns, and surgical history in the previous week. Participants who have already received PCI or CABG or have received other vascular (including cardiocerebral vascular and peripheral vascular) interventional treatments. Uncontrolled hypertension (occasional resting blood pressure higher than 160/100 mmHg in one week, under drug control), severe ventricular arrhythmia, and III-degree atrioventricular block. Other heart diseases such as rheumatic heart disease, pulmonary heart disease, hyperthyroidism heart disease, dilated cardiomyopathy, hypertrophic cardiomyopathy, severe valvular disease, myocarditis, and pericarditis. Participants with aortic dissection, aortic aneurysms, pulmonary embolism, and severe myocardial bridge. Participants with acute exacerbation of chronic obstructive pulmonary disease and respiratory failure. Participants with liver dysfunction and alanine aminotransferase (ALT)>3 times the normal value or combined with cirrhosis; with kidney dysfunction and estimated glomerular filtration rate (eGFR)<30 mL/min/1.73 m2. Participants with hematopoietic system disease, malignant tumor, autoimmune disorders, and infectious disease (tuberculosis, viral hepatitis, syphilis, and acquired immune deficiency syndrome). Participants with acute cerebral stroke and severe complications of diabetes (diabetic foot, diabetic ketoacidosis). Participants with organ transplantation. Participants with psychosis or dysgnosia. Pregnant or lactating women.

3.5. Sample Size

In the multifactor statistical analysis, the sample size is usually 5-10 times of the number of variables [11]. In actual use, there have been some false-positive and false-negative errors. In addition, to improve accuracy, the overall sample size is usually designed to be 20-30 times of the number of variables (items in the scale). This study contains approximately 100 variables. Considering a nonresponse rate of at least 15%, the final overall sample design is estimated as 100 × 25 × (1 + 15%) ≈ 3000 cases, with a 95% confidence interval and 2% relative error.

3.6. Observational Content

The observational content would include (1) demographics: age, sex, home address, education, height, and weight; (2) life style: smoking history and alcohol consumption history; (3) past medical history; (4) medication history; (5) TCM symptoms: the main complaint, feeling of coldness or fever, perspiration, discomfort in parts of body from head to toe, appetite, quality of sleep, stool, urine, the condition of the tongue and pulse, and so on; (6) TCM Zheng; (7) clinical diagnosis; (8) CAG result; and (9) GRACE score.

4. Quality Control

Quality control is crucial in a multicenter study to ensure the accuracy and authenticity. Quality control measures chiefly include organization structure, investigator training, standard operating procedures (SOP), and supervision and internal inspection.

4.1. Organization Structure

The multicenter clinical study will be directed and coordinated by the project leader. In addition, the principle investigator (PI) of every site will be responsible for the assignment of work and the quality control of this study. Meanwhile, a study monitor, who is not directly involved in participant enrollment and information collection, will be authorized by the project leader to supervise this study.

4.2. Investigators Training

Before starting the clinical study, all the investigators should participate in strict and systematic training to ensure the accuracy of participant information. We will carry out intensive training or online video training for all investigators; the training contents include (1) aim, method and SOP; (2) the standardized process for completing the clinical questionnaire; (3) eCRF usage; and (4) information and data management.

4.3. Standard Operating Procedures

4.3.1. Completing the Clinical Questionnaire

(1) To be familiar with the operating procedures, the investigators are expected to read the entire content of the eCRF, instructions on program implementation, and the investigator's handbook carefully before starting the clinical study. (2) Each investigator will have his own separate eCRF account (website: www.medresman.org) to timely, accurately, and thoroughly record each item according to a unified recording method. (3) After recording is complete, each investigator should double-check the information to ensure that there are no omissions or misinformation. (4) If any content in the questionnaire needs to be modified, investigators should indicate the reason for the revision. In addition, any modification process will be recorded by eCRF.

4.3.2. Collecting TCM Symptoms

(1) In the process of collecting clinical information, the investigator should listen patiently and record information carefully. In addition, language should be easily understood by patients, and the use of complicated terminology should be avoided. (2) Each symptom will be divided into four degrees, including “no”, “light”, “medium”, and “heavy”. The instruction of how to classify the degree of each symptom is included in the investigator's handbook. (3) When observing the body and tongue, the investigator should fully expose the parts of the body and examine them under nature light, avoiding the use of colored light. Each tongue should be observed for no more than 30 seconds. If the primary observation of the tongue is not confirmed, patients should rest for 3-5 minutes and investigator may repeat the observation. At this point, for the tongue diagnosis, investigators may refer to the color map in their handbook. (4) Pulse diagnosis is conducted with the radial artery by an experienced TCM practitioner.

4.3.3. Collecting CAG Result and GRACE Score

The CAG result will be judged by the imaging physician. The unified quality control method will be employed to guarantee the accuracy of the GRACE score of each participant, according to international grading standards [12].

4.3.4. Information Management

(1) Patient code: every site has a 2-digit code (Table 1). According to the patient's enrollment order, the corresponding code will be produced. For instance, when Guang'anmen Hospital recruits the first patient, the code will be 01-0001. (2) Dynamic management: by using eCRF, the registration information of the patient will be uploaded synchronously, which will make it simple for the PI to check it in real time. (3) Data collection: to ensure the objectivity and accuracy of the collected data, we recommend that at least two investigators oversee data collection. The diagnosis of the tongue and pulse must be performed by at least two experienced TCM practitioners, and the CAG results should be interpreted by at least two experienced imaging physicians. If there is any disagreement, it will be resolved by discussion and be arbitrated by a third physician. (4) Data entry: all data must be completed by the investigators using the eCRF procedure within 24 of enrollment to ensure accuracy of the data. (5) Data submission: before submitting the eCRF, it should be approved by the PI in charge of the specific site.

4.4. Supervision and Internal Inspection

(1) The monitor will randomly conduct on-site or telephone supervision of the sites and ensure that the study is strictly following the protocol. (2) Content for supervision includes informed consent, standardized collection of clinical information, and accuracy of the raw data. (3) The PI of each site should regularly conduct internal inspections to find and resolve problems in timely manner.

5. Statistical Analysis

All data will be exported in an Excel-format through the www.medresman.org. The methods for statistical analysis include frequency analysis, factor analysis, cluster analysis, decision tree, and other relevant analytic methods. SPSS 20.0 will be used for statistical analysis.

6. Discussion

CHD is usually caused by atherosclerosis, which leads to coronary artery stenosis and myocardial ischemia. The treatment strategies for CHD include mainly drugs, PCI, and CABG. It is notable that different degree of coronary artery stenosis may bring about different clinical manifestations and outcomes. In general, patients with atherosclerosis do not have symptoms of chest pain; patients with borderline coronary lesion could manifest as stable angina; patients scheduled to undergo PCI or CABG or those unable to undergo revascularization have similar symptoms including acute coronary syndrome. Studies have indicated that some kinds of TCM Zheng, such as Qi deficiency, Yin deficiency, Yang deficiency, blood stasis, phlegm, and Qi stagnation, may be found in patients with CHD [13]. Within the framework of TCM theory, different TCM Zheng has different clinical manifestations. For instance, the CHD patient with Qi deficiency could present with chest distress, shortness of breath, lassitude, spontaneous sweating, pale tongue with white coating, and weak pulse. In addition, the CHD patient with blood stasis could manifest symptoms such as a steady stabbing pain in the chest, dark complexion, cyanotic lips and nails, scaly skin, subcutaneous ecchymosis, dark and purple tongue with ecchymosis or spots, thread, and rough or knotted and intermittent pulse. Coronary artery stenosis involves several pathophysiological aspects such as endothelial injury, lipid accumulation, intraplaque hemorrhage, platelet aggregation, and thrombogenesis, which, from the perspective of TCM Zheng, could be prevented; blood stasis and phlegm could be addressed within the framework of TCM theory [14]. Previous cross-sectional studies have often analyzed the relationship between TCM Zheng and CHD, and the inclusion criteria usually used computed tomography angiography to diagnose CHD [15]. However, in this study, we focus on CHD patients who are diagnosed by the golden standard of CAG. We are expanding the population of participants to include not only CHD patients with more than 50% coronary stenosis but also patients with simple atherosclerosis and those with 30%-50% coronary stenosis [16]. In recent years, relevant studies have found that some patients with ACS are diagnosed with normal arteries, which may result from microvascular disease and endothelial dysfunction [17]. Therefore, we hope to see if differences among varying degrees of coronary artery stenosis can be identified in TCM Zheng, which may help indicate if TCM Zheng could identify risk factors for the progression of coronary artery stenosis. The possible association between TCM Zheng and coronary artery stenosis is shown in Figure 2. Among the studies assessing TCM Zheng in CHD, we are the first to assess the GRACE score of participants, which may predict long-term cardiovascular endpoint events [18] and identify those associated with different TCM Zheng.
Figure 2

The possible association between TCM Zheng and coronary artery stenosis.

  15 in total

1.  ACC/AHA guidelines for coronary angiography. A report of the American College of Cardiology/American Heart Association Task Force on practice guidelines (Committee on Coronary Angiography). Developed in collaboration with the Society for Cardiac Angiography and Interventions.

Authors:  P J Scanlon; D P Faxon; A M Audet; B Carabello; G J Dehmer; K A Eagle; R D Legako; D F Leon; J A Murray; S E Nissen; C J Pepine; R M Watson; J L Ritchie; R J Gibbons; M D Cheitlin; T J Gardner; A Garson; R O Russell; T J Ryan; S C Smith
Journal:  J Am Coll Cardiol       Date:  1999-05       Impact factor: 24.094

2.  Pathophysiology and management of patients with chest pain and normal coronary arteriograms (cardiac syndrome X).

Authors:  Juan Carlos Kaski
Journal:  Circulation       Date:  2004-02-10       Impact factor: 29.690

Review 3.  Traditional Chinese Medicine for Cardiovascular Disease: Evidence and Potential Mechanisms.

Authors:  Panpan Hao; Fan Jiang; Jing Cheng; Lianyue Ma; Yun Zhang; Yuxia Zhao
Journal:  J Am Coll Cardiol       Date:  2017-06-20       Impact factor: 24.094

4.  Analysis on outcome of 5284 patients with coronary artery disease: the role of integrative medicine.

Authors:  Zhu-ye Gao; Hao Xu; Da-zhuo Shi; Chuan Wen; Bao-yan Liu
Journal:  J Ethnopharmacol       Date:  2011-09-08       Impact factor: 4.360

5.  Clinical epidemiology survey of the traditional Chinese medicine etiology and syndrome differentiation of coronary artery disease: study protocol of a multicenter trial.

Authors:  Ying-fei Bi; Jing-yuan Mao; Xian-liang Wang; Ya-zhu Hou; Yi-zhu Lu; Shan Bin Soh; Bo-li Zhang
Journal:  Zhong Xi Yi Jie He Xue Bao       Date:  2012-06

6.  Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE).

Authors:  Keith A A Fox; Omar H Dabbous; Robert J Goldberg; Karen S Pieper; Kim A Eagle; Frans Van de Werf; Alvaro Avezum; Shaun G Goodman; Marcus D Flather; Frederick A Anderson; Christopher B Granger
Journal:  BMJ       Date:  2006-10-10

7.  Study on syndrome element characteristics and its correlation with coronary angiography in 324 patients with coronary heart disease.

Authors:  Jie WANG; Fu-yong CHU; Jun LI; Kui-wu YAO; Jing-bai ZHONG; Ke-hua ZHOU; Qing-yong HE; Xiao-wei SUN
Journal:  Chin J Integr Med       Date:  2008-12-12       Impact factor: 1.978

Review 8.  A network-based analysis of the types of coronary artery disease from traditional Chinese medicine perspective: potential for therapeutics and drug discovery.

Authors:  Wei Zhou; Yonghua Wang
Journal:  J Ethnopharmacol       Date:  2013-11-20       Impact factor: 4.360

Review 9.  Korean studies on blood stasis: an overview.

Authors:  Bongki Park; Sooseong You; Jeeyoun Jung; Ju Ah Lee; Kyung-Jin Yun; Myeong Soo Lee
Journal:  Evid Based Complement Alternat Med       Date:  2015-03-02       Impact factor: 2.629

10.  Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010.

Authors:  Rafael Lozano; Mohsen Naghavi; Kyle Foreman; Stephen Lim; Kenji Shibuya; Victor Aboyans; Jerry Abraham; Timothy Adair; Rakesh Aggarwal; Stephanie Y Ahn; Miriam Alvarado; H Ross Anderson; Laurie M Anderson; Kathryn G Andrews; Charles Atkinson; Larry M Baddour; Suzanne Barker-Collo; David H Bartels; Michelle L Bell; Emelia J Benjamin; Derrick Bennett; Kavi Bhalla; Boris Bikbov; Aref Bin Abdulhak; Gretchen Birbeck; Fiona Blyth; Ian Bolliger; Soufiane Boufous; Chiara Bucello; Michael Burch; Peter Burney; Jonathan Carapetis; Honglei Chen; David Chou; Sumeet S Chugh; Luc E Coffeng; Steven D Colan; Samantha Colquhoun; K Ellicott Colson; John Condon; Myles D Connor; Leslie T Cooper; Matthew Corriere; Monica Cortinovis; Karen Courville de Vaccaro; William Couser; Benjamin C Cowie; Michael H Criqui; Marita Cross; Kaustubh C Dabhadkar; Nabila Dahodwala; Diego De Leo; Louisa Degenhardt; Allyne Delossantos; Julie Denenberg; Don C Des Jarlais; Samath D Dharmaratne; E Ray Dorsey; Tim Driscoll; Herbert Duber; Beth Ebel; Patricia J Erwin; Patricia Espindola; Majid Ezzati; Valery Feigin; Abraham D Flaxman; Mohammad H Forouzanfar; Francis Gerry R Fowkes; Richard Franklin; Marlene Fransen; Michael K Freeman; Sherine E Gabriel; Emmanuela Gakidou; Flavio Gaspari; Richard F Gillum; Diego Gonzalez-Medina; Yara A Halasa; Diana Haring; James E Harrison; Rasmus Havmoeller; Roderick J Hay; Bruno Hoen; Peter J Hotez; Damian Hoy; Kathryn H Jacobsen; Spencer L James; Rashmi Jasrasaria; Sudha Jayaraman; Nicole Johns; Ganesan Karthikeyan; Nicholas Kassebaum; Andre Keren; Jon-Paul Khoo; Lisa Marie Knowlton; Olive Kobusingye; Adofo Koranteng; Rita Krishnamurthi; Michael Lipnick; Steven E Lipshultz; Summer Lockett Ohno; Jacqueline Mabweijano; Michael F MacIntyre; Leslie Mallinger; Lyn March; Guy B Marks; Robin Marks; Akira Matsumori; Richard Matzopoulos; Bongani M Mayosi; John H McAnulty; Mary M McDermott; John McGrath; George A Mensah; Tony R Merriman; Catherine Michaud; Matthew Miller; Ted R Miller; Charles Mock; Ana Olga Mocumbi; Ali A Mokdad; Andrew Moran; Kim Mulholland; M Nathan Nair; Luigi Naldi; K M Venkat Narayan; Kiumarss Nasseri; Paul Norman; Martin O'Donnell; Saad B Omer; Katrina Ortblad; Richard Osborne; Doruk Ozgediz; Bishnu Pahari; Jeyaraj Durai Pandian; Andrea Panozo Rivero; Rogelio Perez Padilla; Fernando Perez-Ruiz; Norberto Perico; David Phillips; Kelsey Pierce; C Arden Pope; Esteban Porrini; Farshad Pourmalek; Murugesan Raju; Dharani Ranganathan; Jürgen T Rehm; David B Rein; Guiseppe Remuzzi; Frederick P Rivara; Thomas Roberts; Felipe Rodriguez De León; Lisa C Rosenfeld; Lesley Rushton; Ralph L Sacco; Joshua A Salomon; Uchechukwu Sampson; Ella Sanman; David C Schwebel; Maria Segui-Gomez; Donald S Shepard; David Singh; Jessica Singleton; Karen Sliwa; Emma Smith; Andrew Steer; Jennifer A Taylor; Bernadette Thomas; Imad M Tleyjeh; Jeffrey A Towbin; Thomas Truelsen; Eduardo A Undurraga; N Venketasubramanian; Lakshmi Vijayakumar; Theo Vos; Gregory R Wagner; Mengru Wang; Wenzhi Wang; Kerrianne Watt; Martin A Weinstock; Robert Weintraub; James D Wilkinson; Anthony D Woolf; Sarah Wulf; Pon-Hsiu Yeh; Paul Yip; Azadeh Zabetian; Zhi-Jie Zheng; Alan D Lopez; Christopher J L Murray; Mohammad A AlMazroa; Ziad A Memish
Journal:  Lancet       Date:  2012-12-15       Impact factor: 79.321

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